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For Companies At a Glance
- Tasks: Explore customer data, develop AI use cases, and engage with stakeholders to drive scientific innovation.
- Company: Join TetraScience, a leader in Scientific Data and AI revolutionising lab data management.
- Benefits: Enjoy competitive salary, equity, generous PTO, and remote work options.
- Why this job: Make a real impact in life sciences by bridging science and technology.
- Qualifications: PhD with 15+ years in life sciences and strong coding skills.
- Other info: Collaborative culture focused on continuous improvement and scientific transformation.
The predicted salary is between 72000 - 108000 ÂŁ per year.
Who We Are
TetraScience is the Scientific Data and AI company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next‑gen lab data management solutions, scientific use cases, and AI‑enabled outcomes. TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de‑facto standard, entering into co‑innovation and go‑to‑market partnerships.
In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our co‑founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective. It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day.
Who You Are
You are a strategic, analytically minded professional with a passion for bridging scientific insights and cutting‑edge technology. You thrive in environments where you can collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes. With deep domain knowledge in drug discovery/preclinical development, CMC, or Quality, you are skilled at uncovering innovative use cases that drive AI and machine learning applications. Your ability to engage with scientists and business leaders alike makes you a key player in maximizing the value of scientific data. You will need to be a high clock speed and forward‑thinking individual with a passion for developing requirements for complex solutions targeted to R&D and Quality personas inside Life Sciences. You should also be energized by regularly working onsite with customers. You thrive in dynamic, high‑impact, face‑to‑face collaborative environments where you can build deep relationships and drive scientific transformation firsthand.
Requirements
- PhD with 15+ years of industry experience in life sciences, preferably across pharma, biotech, or health tech, with deep domain expertise in discovery, preclinical, CMC, and/or Quality
- Extensive hands‑on experience or direct oversight in one or more of the following areas: high throughput screening, preclinical toxicology, materials engineering, analytical development, drug substance (DS) synthesis and manufacturing
- Delivered requirements for AI/ML‑driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization
- Extensive hands‑on experience with scientific data workflows and lab automation; exposure to FAIR principles and modern data architecture is a plus
- Strong coding or scripting background (e.g., Python, Nextflow, AWS, SDKs) and familiarity with scientific tools, databases, and ontologies is preferred
- Exceptional communication and storytelling ability to engage technical and executive stakeholders
- Prior experience in customer‑facing, consulting, or commercial‑scientific interface roles
What You Will Do
- Customer Data Exploration: Investigate diverse customer datasets, identifying enrichment and AI‑readiness opportunities
- Scientific Use Case Development: Collaborate with customers to define, iterate, and implement innovative scientific AI/ML use cases
- Stakeholder Engagement: Conduct onsite interviews and workshops to deeply understand customer challenges and data landscapes
- Data Analysis and Enrichment: Perform exploratory data analysis and define transformation workflows that enable scientific AI
- Workflow Documentation: Develop visual documentation including workflow diagrams, ERDs, and ontology definitions
- AI Model Evaluation: Provide practical scientific input on model output, with suggestions to improve real‑world performance
- Customer Enablement: Deliver onsite demonstrations, conduct working sessions, and act as a trusted advisor in AI adoption
- Strategic Insight: Propose new directions, experiments, or platforms that can amplify scientific discovery and development
Benefits
Competitive Salary and equity in a fast‑growing company
Supportive, team‑oriented culture of continuous improvement
Generous paid time off (PTO)
Remote working opportunities, when not at customer sites
Scientific Business Analyst - United Kingdom employer: TetraScience
Contact Detail:
TetraScience Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Scientific Business Analyst - United Kingdom
✨Tip Number 1
Get to know TetraScience inside out! Before your interview, read the Tetra Way letter thoroughly. It’s not just a formality; it’ll help you understand the company culture and values, which is crucial for showing you’re a great fit.
✨Tip Number 2
Show off your analytical skills! Be ready to discuss specific examples of how you've transformed complex scientific data into actionable insights. This will demonstrate your ability to bridge the gap between science and technology, which is key for this role.
✨Tip Number 3
Don’t just talk about your experience; engage with your interviewers! Ask insightful questions about their current projects and challenges. This shows you’re genuinely interested and ready to collaborate with their team.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it gives you a chance to showcase your enthusiasm for joining TetraScience right from the start.
We think you need these skills to ace Scientific Business Analyst - United Kingdom
Some tips for your application 🫡
Read the Tetra Way Letter: Before you dive into your application, make sure to read the Tetra Way letter from our CEO, Patrick Grady. It’s super important for understanding our values and whether we’re the right fit for each other.
Tailor Your Application: When writing your application, don’t just send a generic CV and cover letter. Highlight your experience in drug discovery or preclinical development, and show us how your skills align with the role of Scientific Business Analyst.
Show Your Passion for Science and Tech: We love candidates who are passionate about bridging scientific insights with technology. Make sure to include examples of how you've done this in your previous roles, especially if you’ve worked with AI/ML solutions.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people and shows us you’re serious about joining our team!
How to prepare for a job interview at TetraScience
✨Know the Tetra Way
Before your interview, make sure to read and reflect on the Tetra Way letter. This document is crucial for understanding the company's values and ethos. Think about how your own values align with theirs, as this will be a key discussion point during the interview.
✨Showcase Your Domain Expertise
Be prepared to discuss your deep domain knowledge in drug discovery, preclinical development, or Quality. Highlight specific examples from your 15+ years of experience that demonstrate your ability to bridge scientific insights with technology, especially in AI/ML applications.
✨Engage with Real-World Scenarios
During the interview, expect to engage in discussions about customer data exploration and scientific use case development. Prepare to share your experiences in conducting onsite interviews and workshops, and how you’ve tackled customer challenges in the past.
✨Communicate Effectively
Your ability to communicate complex ideas clearly is vital. Practice storytelling techniques to convey your experiences engaging with both technical and executive stakeholders. Be ready to explain how you've delivered requirements for AI-driven solutions in a way that resonates with diverse audiences.
